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  • Title: Predictors of survival following liver transplantation in infants: a single-center analysis of more than 200 cases.
    Author: Venick RS, Farmer DG, McDiarmid SV, Duffy JP, Gordon SA, Yersiz H, Hong JC, Vargas JH, Ament ME, Busuttil RW.
    Journal: Transplantation; 2010 Mar 15; 89(5):600-5. PubMed ID: 19997060.
    Abstract:
    BACKGROUND: Infants (<12 months) who require liver transplantation (LTx) represent a particularly challenging and understudied group of patients. METHODS: This retrospective study aimed to describe a large single-center experience of infants who received isolated LTx, illustrate important differences in infants versus older children, and identify pretransplant factors which influence survival. More than 25 pre-LTx demographic, laboratory, and operative variables were analyzed using the Log-rank test and Cox proportional hazards model. RESULTS: Between 1984 and 2006, 216 LTx were performed in 186 infants with a mean follow-up time of 62 months. Median age at LTx was 9 months, the majority had cholestatic liver disease, were hospitalized pre-LTx, and received whole grafts. Leading indications for re-LTx (n=30) included vascular complications (43%) and graft nonfunction (40%), whereas leading causes of death were sepsis and multiorgan failure. One-, 5-, and 10-year graft and patient survivals were 75%/72%/68% and 79%/77%/75%, respectively. Relative to older pediatric recipients, infants had worse overall patient survival (P=0.05). The following were significant univariate predictors of graft loss: age less than 6 months and reduced cadaveric grafts; and of patient loss: age less than 6 months, calculated CrCl less than 90, pre-LTx hospitalization, pre-LTx mechanical ventilation, repeat LTx, infants transplanted for reasons other than cholestatic liver disease, and patients transplanted between 1984 and 1994. CONCLUSIONS: Long-term outcomes for infants undergoing LTx are excellent and have improved over time. As the largest, single-center analysis of LTx in infants, this study elucidates a unique set of predictors that can aid in medical decision making.
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